A computational investigation into the human representation and processing of visual information.

    I'm here to tell you it is not. In fact, fundamental poker math is very easy to learn. More importantly, it can yield you a lot more profits at the poker table. Without using simple math at the poker table, you are simply playing a guessing game. Use Simple Math at the Poker Table and Increase You Winnings In this book I will teach you how to use simple arithmetic at the poker table to gain a huge skill advantage over your opponents that will allow you to win more and lose less. Poker players that don't use math are simply guessing and you'll learn to no longer guess and know the right mathematical move at the poker table. These simple mathematical concepts I will be teaching you will drastically help improve your poker game and allow you to make the most profitable decisions at the poker. Contents and Overview First you will be introduced to some fundamental overarching poker concepts that apply to poker mathematics. Then we will begin our journey into poker mathematics where you will learn about probabilities and odds, pot odds and implied odds, pot equity, and expected value. You will then learn how to quickly estimate your equity at the poker table using the Rule of 2 & 4. Moreover, you'll learn the steps involved in determining if calling with a drawing hand is profitable or not. We will also cover how to size your bets with the best hand and teach you how often bluffs and hero calls need to work to be profitable. Lastly, we will show you how to perform EV calculations and better understand card combinations. Effectively Understand and Utilize Essential Poker Math Develop a keen understanding of Probability and Odds Learn to quickly calculate Pot Odds & Implied Odds at the poker table Effectively use Pot Equity & The Rule of 2 & 4 to Determine the correct poker play Understand how to use Expected Value (EV) both on and off the table to analyze your plays Learn the important math behind Bluffs & Hero Calls to give you a skill advantage over your opponent Learn Card Combinations to further enhance your card reading abilities And Many More Amazing Topics… What You Will Get out of This Book Suitable for both beginning and experienced poker players alike you'll learn many essential fundamental poker mathematical concepts that will help you drastically improve your poker game. After reading this book, you will have mastered fundamental No Limit Holdem mathematics. You will have gained a huge skill advantage over your opponents and you will be able to quickly and effectively use math at the poker table to make are always the most profitable move. Most importantly, you will become a much better and profitable poker player! So what are you waiting for? Purchase this book today to start learning how to advance your poker game with simple poker math! Alton Hardin is the founder of MicroGrinder.com, a free micro stakes poker website that is dedicated to helping micro stakes poker players improve their poker game by offering a wide array of free and low-cost resources including poker courses, poker t

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    But can machines really think? Is the mind just a complicated computer program? Introducing Artificial Intelligence focuses on the issues behind one of science's most difficult problems.

    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

    This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

    

    AI is all the rage, and the buzziest AI buzz surrounds adaptive machine learning computer systems that learn intelligent behavior from massive amounts of data. This is what powers a driverless car, for example. In this book, Hector Levesque shifts the conversation to -good old fashioned artificial intelligence, - which is based not on heaps of data but on understanding commonsense intelligence. This kind of artificial intelligence is equipped to handle situations that depart from previous patterns -- as we do in real life, when, for example, we encounter a washed-out bridge or when the barista informs us there's no more soy milk.Levesque considers the role of language in learning. He argues that a computer program that passes the famous Turing Test could be a mindless zombie, and he proposes another way to test for intelligence -- the Winograd Schema Test, developed by Levesque and his colleagues. -If our goal is to understand intelligent behavior, we had better understand the difference between making it and faking it, - he observes. He identifies a possible mechanism behind common sense and the capacity to call on background knowledge: the ability to represent objects of thought symbolically. As AI migrates more and more into everyday life, we should worry if systems without common sense are making decisions where common sense is needed.

    In the beginning was Josh Levine, an idealistic programming genius who dreamed of wresting control of the market from the big exchanges that, again and again, gave the giant institutions an advantage over the little guy. Levine created a computerized trading hub named Island where small traders swapped stocks, and over time his invention morphed into a global electronic stock market that sent trillions in capital through a vast jungle of fiber-optic cables. By then, the market that Levine had sought to fix had turned upside down, birthing secretive exchanges called dark pools and a new species of trading machines that could think, and that seemed, ominously, to be slipping the control of their human masters. Dark Pools is the fascinating story of how global markets have been hijacked by trading robots--many so self-directed that humans can't predict what they'll do next.

    Most important, it provides a wealth of examples for readers to model for everything from online journal articles to supplemental data sets and measurement instruments to books, videos, apps, websites, podcasts, blog posts, and social media. Approximately 70 examples are provided for readers to consider as they learn how to create reliable references for electronic sources.Students and other writers will find this guide indispensable as well as convenient to download and use when creating a reference list.

     Written by Wayne Booth, author of the seminal book, The Rhetoric of Fiction (1961). Explores the consequences of bad rhetoric in education, in politics, and in the media. Investigates the possibility of reducing harmful conflict by practising a rhetoric that depends on deep listening by both sides.

    In this 148-page hardback they reveal the places that they have got to know and love and show you why Tokyo is the friendliest big city in the world. It’s a guide book that will lead you to the best in culture and new architecture – and a few fun nights out too.The Monocle Travel Guide series reveals our favourite places in each city we cover, from the ideal route for an early-morning run to the best spots for independent retail. Full of surprises and quirks, they also feature detailed design and architecture pages, neighbourhood walks to get you away from the crowds and our favourite places to eat everything be it tasty fast food or something truly celebratory.

    You'll also receive updates when significant changes are made, as well as the final ebook version. Embedded Android is for Developers wanting to create embedded systems based on Android and for those wanting to port Android to new hardware, or creating a custom development environment. Hackers and moders will also find this an indispensible guide to how Android works.

    Covering all of the fundamentals in a straightforward, student-friendly manner, it is ideal for undergraduate- and graduate-level courses across the social sciences and also serves as an indispensable guide for researchers. Striking a balance between specific techniques and the underlying logic of scientific inquiry, this book provides a lucid treatment of the four major approaches to research: experimentation, survey research, field research, and the use of available data. Richly developed examples of empirical research and an emphasis on the research process enable students to better understand the real-world application of research methods. The authors also offer a unique chapter (13) advocating a multiple-methods strategy.

    Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud-computing technologies. This collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.